precipitation simulation data

The dataset used in this study includes one dependent variable—seasonal average precipitation for autumn—and several independent variables representing terrain characteristics. The precipitation data, sourced from the National Tibetan Plateau Data Center, are high-resolution monthly precipitation records for China with a spatial resolution of approximately 1 km, averaged over September to November 2018. The terrain-related independent variables include elevation (derived from a 30-meter resolution digital elevation model), slope (calculated based on elevation change rates), terrain undulation (computed as the standard deviation of elevation within a 12 km radius), main wind direction coefficient (calculated from the angle between slope aspect and prevailing wind direction), and distance to the coastline (shortest distance from each point to the coastline). These variables comprehensively capture the region’s topographic complexity and land-sea distribution, providing a rich data foundation for analyzing the spatial distribution of precipitation and its relationship with terrain.